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Building RESTful APIs With Flask: An ORM With SQLAlchemy

This tutorial continues our three-part series on building RESTful APIs with Flask. Part one demonstrated building APIs directly with Flask, offering flexibility but requiring significant code. This part streamlines the process using Flask-Restless,

Mar 09, 2025 am 11:47 AM

Mathematical Modules in Python: Statistics

Python's statistics module provides powerful data statistical analysis capabilities to help us quickly understand the overall characteristics of data, such as biostatistics and business analysis. Instead of looking at data points one by one, just look at statistics such as mean or variance to discover trends and features in the original data that may be ignored, and compare large datasets more easily and effectively. This tutorial will explain how to calculate the mean and measure the degree of dispersion of the dataset. Unless otherwise stated, all functions in this module support the calculation of the mean() function instead of simply summing the average. Floating point numbers can also be used. import random import statistics from fracti

Mar 09, 2025 am 11:40 AM

Building RESTful APIs With Flask: ORM Independent

This tutorial concludes a three-part series on building RESTful APIs with Flask, demonstrating an ORM-agnostic approach using Flask-Restful. Unlike the previous installments which relied on SQLAlchemy, this method abstracts the Object-Relational Map

Mar 09, 2025 am 10:46 AM

Mathematical Modules in Python: Decimal and Fractions

Even the most basic mathematical operations can sometimes produce wrong results. This is due to the limitations in storing the exact values of certain numbers. You can overcome these limitations by using the decimal module in Python. Similarly, neither the math and cmath modules we learned in the previous tutorial can help us perform fraction-based arithmetic operations. However, the fractions module in Python happens to do just that. This tutorial will cover these two modules and the different functions they provide. Using the Decimal module from decimal import Decimal Decimal(121) # Return Decimal('12

Mar 09, 2025 am 09:15 AM

How to Work With Excel Documents Using Python

I believe you have used Microsoft Excel on some occasions. It is very powerful when it comes to working with spreadsheets, tables, charts, etc. But what does Python have to do with that?Python is a game-changer when it comes to Excel files because it

Mar 08, 2025 am 10:45 AM

Scraping Webpages in Python With Beautiful Soup: Search and DOM Modification

This tutorial builds upon the previous introduction to Beautiful Soup, focusing on DOM manipulation beyond simple tree navigation. We'll explore efficient search methods and techniques for modifying HTML structure. One common DOM search method is ex

Mar 08, 2025 am 10:36 AM

Serialization and Deserialization of Python Objects: Part 1

Serialization and deserialization of Python objects are key aspects of any non-trivial program. If you save something to a Python file, you do object serialization and deserialization if you read the configuration file, or if you respond to an HTTP request. In a sense, serialization and deserialization are the most boring things in the world. Who cares about all these formats and protocols? You want to persist or stream some Python objects and retrieve them in full at a later time. This is a great way to see the world on a conceptual level. However, on a practical level, the serialization scheme, format or protocol you choose may determine the speed, security, freedom of maintenance status, and other aspects of the program

Mar 08, 2025 am 09:39 AM